🌿 Project Kalos: High-Performance C/CUDA Neuromorphic Engine Suite

💥 Key Features & Performance Highlights

• O(1) Microsecond Memory Recall (465.12 μs): Replaces linear text re-tokenization (20,441.90 ms) with constant-time CUDA vector lookup.
• 7.25x Faster Total Response Completion (72B Models): Cuts total user-sent to output-completion latency on 72B parameter models from 23.71 seconds down to 3.27 seconds.
• 99.8% VRAM Footprint Reduction: Compresses 16.38 GB KV-cache bloat down to 2.50 MB of sparse associative neural templates.
• Sub-Millisecond Reflex Sentry (15.16 μs): 4.19-Million CUDA spiking neurons for instant event detection.
• Native Physical Haptics: Real-time CUDA perception for physical touch contact, localized warmth, and FFT audio spectrum resonance.
• Stateful Identity Persistence (.soul): Compact 2.5 MB binary cortical persistence format.

🛠️ Quick Start & Running Precompiled Release Binaries

1. Clone the Repository

2. System Requirements

• Linux OS (Ubuntu 22.04+ recommended)
• NVIDIA GPU with CUDA Driver 12.0+ installed
• Python 3.10+ (for telemetry monitor scripts)

3. Run Precompiled Executables

• Interactive Terminal UI (TUI):
  ./bin/kalos_tui
• Hardware Telemetry Profiler:
  ./bin/kalos_bench
• Fast In-Memory CUDA Executor:
  ./bin/kalos_runner

4. Shared C/CUDA Libraries (./bin/)

• libkalos_snn.so: Spiking Neural Cortex Engine (15.16 μs LIF Cortex)
• libkalos_sam.so: Sparse Associative Memory Engine (465.12 μs Vector Recall)
• libkalos_haptics.so: Physical Touch & FFT Audio Engine
• libkalos_soul.so: Binary Cortical Persistence Format (.soul)

📄 Release Documentation & Whitepapers

• docs/Whitepaper_Industrial.html: Master Industrial Release HTML Whitepaper (Amber / Crimson CRT Theme).
• docs/WHITE_PAPER.md: Complete Master Architectural & Empirical Markdown Whitepaper.
• docs/BENCHMARK_REPORT.md: Detailed Empirical Benchmark Matrix (7B to 72B Models).
• docs/SETUP_GUIDE.md: Comprehensive Integration & Configuration Guide.

📜 License, Attribution & Contact

• License: Licensed under the MIT License.
• Authors: Mongoose & Kalos Engine Architecture Team @ BlackForest Studio (2026).
• Contact & Inquiries: blackforest.team@proton.me
• Hugging Face Hub: https://huggingface.co/MongooseReborn/kalos-engine
• GitHub Repository: https://github.com/MongooseReborn/kalos-engine